Software applications and systems have become indispensable tools for helping consumers, i.e., users, perform a wide variety of tasks in their daily professional and personal lives. Currently, numerous types of desktop, web-based, and cloud-based software systems are available to help users perform a plethora of tasks ranging from basic computing system operations and word processing, to financial management, small business management, tax preparation, health tracking and healthcare management, as well as other personal and business endeavors, operations, and functions far too numerous to individually delineate here.
One major, if not determinative, factor in the utility, and ultimate commercial success, of a given software system of any type is the ability to implement and provide a customer support system through which a given user can obtain assistance and, in particular, get answers to questions that arise during the installation and operation of the software system. However, providing potentially millions of software system users specialized advice and answers to their specific questions is a huge undertaking that can easily, and rapidly, become economically infeasible.
To address this problem, many providers of software systems implement or sponsor one or more question and answer based customer support systems. Typically, a question and answer based customer support system includes a hosted forum through which a user can direct their specific questions, typically in a text format, to a support community that often includes other users and/or professional support personal.
In many cases, once a user's specific question is answered by members of the support community through the question and answer based customer support system, the user's specific question, and the answer to the specific question provided by the support community, is categorized and added to a customer support question and answer database associated with the question and answer based customer support system. In this way, subsequent users of the software system can access the user's specific question or topic, and find the answer to the user's question, via a search of the customer support question and answer database. As a result, a dynamic customer support question and answer database of categorized/indexed user questions and answers is made available to users of the software system through the question and answer based customer support system.
The development of customer support question and answer databases has numerous advantages including a self-help element whereby a searching user, i.e., a user accessing the resulting question and answer pair, can find an answer to their particular question by simply searching the customer support question and answer database for topics, questions, and answers related to their issue. In addition, if the answer to the user's specific question is not in the customer support question and answer database, the user can then become an asking user by submitting their question to the question and answer based customer support system, typically through the same web-site and/or user interface. Consequently, using a question and answer based customer support system including a customer support question and answer database, potentially millions of user questions can be answered in an efficient and effective manner, and with minimal duplicative effort.
Using currently available question and answer based customer support systems, once an asking user's question is answered, the asking user is provided the opportunity to rate the answer with respect to how helpful the answer was to the asking user. In addition, searching users in the user community are provided the opportunity to access the question and answer data in the customer support question and answer database and then these searching users are also provided the opportunity to rate the accessed question and answer content based on how helpful the answer was to them. In this way, feedback is provided with respect to a given question and answer pair, and answers with low satisfaction ratings, i.e., poorly rated answers, can eventually be identified by this feedback. Typically, a poorly rated answer is then eventually removed from the customer support question and answer database.
However, using current question and answer based customer support systems, and their associated customer support question and answer databases, the poorly rated question and answer content is only removed after it has potentially been viewed by multiple users, and often a large number of searching users. Consequently, by the time poorly rated question and answer content is identified by a threshold number of low satisfaction ratings, such as a “down vote,” of the answer content, not only is the initial asking user potentially dissatisfied with the answer content, and often with the software system itself, but additional searching users, and often numerous additional searching users, are also potentially dissatisfied with the poorly rated question and answer content, as well as the support provided, and the software system itself. In addition, these current methods for identifying poorly rated question and answer content are based on the assumption that the users will not only provide feedback, but that they will provide feedback that is objective and logical, e.g., not based on emotion or frustration; Often, this is simply not the case.
The fact that, currently, poorly rated question and answer content is only removed after it has been viewed, and the answer content voted down by multiple users, and often a large number of users, is a significant issue and a long standing problem for question and answer based customer support systems and software system providers. This is because user satisfaction with the question and answer based customer support systems is not only critical to the effectiveness of the question and answer based customer support systems, but also to the satisfaction and reputation of the software system and the software system provider. Consequently, one of the most significant long standing problems adversely affecting question and answer based customer support systems is the inability to ensure user satisfaction with answer content provided through the question and answer based customer support systems in relative real-time, or at least before multiple users are provided access to low quality question and answer content. The current lack of an efficient and effective solution to this problem means that, currently, both users and providers of software systems, and question and answer based customer support systems of all types, are denied the full potential of question and answer based customer support systems. As a result, the technical fields of information dissemination, customer support, feedback utilization and integration, software implementation and operation, and user experience are detrimentally affected.
What is needed is a method and system for reliably and efficiently predicting answer quality, and user satisfaction with a potential answer to the user's question, before the answer to the question is generated and provided to users. In this way, not only can the individual asking user's satisfaction with an answer be predicted before the answer is provided to the user, but the satisfaction of other searching users with the question and answer content can be predicted to ensure answers likely to result in poor user satisfaction ratings are never provided to the users.